Effects of metformin on recognition memory and hippocampal neuroplasticity in rats with metabolic syndrome

Metabolic syndrome (MS) is a health problem that is characterized by body fat accumulation, hypertension, dyslipidemia, and hyperglycemia; recently, it has been demonstrated that MS also damages memory processes. The first-line drug in the treatment of MS and type 2 diabetes mellitus is metformin, which is an antihyperglycemic agent. This drug has been shown to produce neuroprotection and to improve memory processes. However, the mechanism involved in this neuroprotection is unknown. A 90-day administration of metformin improved the cognitive processes of rats with MS as evaluated by the novel object recognition test, and this finding could be explained by an increase in the neuronal spine density and spine length. We also found that metformin increased the immunoreactivity of synaptophysin, sirtuin-1, AMP-activated protein kinase, and brain-derived neuronal factor, which are important plasticity markers. We conclude that metformin is an important therapeutic agent that increases neural plasticity and protects cognitive processes. The use of this drug is important in the minimization of the damage caused by MS.     

A new approach for sizing trials with composite binary endpoints using anticipated marginal values and accounting for the correlation between components

Composite binary endpoints are increasingly used as primary endpoints in clinical trials. When designing a trial, it is crucial to determine the appropriate sample size for testing the statistical differences between treatment groups for the primary endpoint. As shown in this work, when using a composite binary endpoint to size a trial, one needs to specify the event rates and the effect sizes of the composite components as well as the correlation between them. In practice, the marginal parameters of the components can be obtained from previous studies or pilot trials; however, the correlation is often not previously reported and thus usually unknown. We first show that the sample size for composite binary endpoints is strongly dependent on the correlation and, second, that slight deviations in the prior information on the marginal parameters may result in underpowered trials for achieving the study objectives at a pre-specified significance level. We propose a general strategy for calculating the required sample size when the correlation is not specified and accounting for uncertainty in the marginal parameter values. We present the web platform CompARE to characterize composite endpoints and to calculate the sample size just as we propose in this paper. We evaluate the performance of the proposal with a simulation study and illustrate it by means of a real case study using CompARE.     

Liver involvement in hereditary hemorrhagic telangiectasia (HHT)

Liver involvement in hereditary hemorrhagic telangiectasia (HHT) consists of extensive intrahepatic vascular malformations associated with blood shunting (arteriovenous, arterioportal and/or portovenous). It is a rare disorder that nevertheless can result in significant systemic and hepatobiliary abnormalities. Although hepatic vascular malformations are present in a majority of patients with HHT, symptoms occur in a only a minority with a clear predominance for the female gender. Symptoms from liver vascular malformations are often misdiagnosed and this can lead to potentially harmful interventions. In this review article, clinical findings of liver involvement in HHT and their pathophysiology are discussed as well as diagnostic methodologies, therapies used and their outcome. Data presented is based on a review of the literature performed in October 2006 using the following MEDLINE search terms: (hereditary hemorrhagic telangiectasia [ALL] OR Rendu-Osler-Weber [ALL]) AND (liver OR hepatic [ALL]). Papers were considered if they were published in English and if they included specific cases that were sufficiently described.